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  • mysql_fetch_array() not displaying all results

    - by user1666995
    I have a database with a calendar table (each row represents one day) with 4 years of rows (2012, 2013, 2014, 2015). I use the column name calyear for the year. I use the following code to find values for distinct years then display it: $year = mysql_query("SELECT DISTINCT calyear FROM calendar"); while($yeararray = mysql_fetch_array($year)) { echo($yeararray['calyear']."<br />"); } The problem is it only displays the years 2013, 2014, 2015 even though when I use echo(mysql_num_rows($year); it displays the value 4 which I take to mean all 4 years are there. I'm not quite sure where I'm going wrong with this.

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  • MySQL "IS IN" equivalent?

    - by nute
    A while ago I worked on a MS-SQL project and I remember a "IS IN" thing. I tried it on a MySQL project and it did not work. Is there an equivalent? Workaround? Here is the full query I am trying to run: SELECT * FROM product_product, product_viewhistory, product_xref WHERE ( (product_viewhistory.productId = product_xref.product_id_1 AND product_xref.product_id_2 = product_product.id) OR (product_viewhistory.productId = product_xref.product_id_2 AND product_xref.product_id_1 = product_product.id) ) AND product_product.id IS IN (SELECT DISTINCT pvh.productId FROM product_viewhistory AS pvh WHERE pvh.cookieId = :cookieId ORDER BY pvh.viewTime DESC LIMIT 10) AND product_viewhistory.cookieId = :cookieId AND product_product.outofstock='N' ORDER BY product_xref.hits DESC LIMIT 10 It's pretty big ... but the part I am interested in is: AND product_product.id IS IN (SELECT DISTINCT pvh.productId FROM product_viewhistory AS pvh WHERE pvh.cookieId = :cookieId ORDER BY pvh.viewTime DESC LIMIT 10) Which basically says I want the products to be in the "top 10" of that sub-query. How would you achieve that with MySQL (while trying to be efficient)?

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  • How to repair "order by" after union of 2 selects from 1 tables

    - by 4e4el
    I have a dropDownList on my form, where i need to have union of values from 2 colums of table [ost]. Type of this columns is currency. I have russian version of access, default value of curency in "rur" and i need "uah". I need to change format and save "order by". I use this query: (SELECT distinct FORMAT([Sum1] ,'# ##0.00" uah.";-# ##0.00" uah."') FROM ost) Union (SELECT distinct FORMAT([Sum2],'# ##0.00" uah.";-# ##0.00" uah."') FROM ost) ORDER BY 1

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  • Entity Framework with SQL Server 2000 (APPLY Operator) issue

    - by How Lun
    Hello, I have a simple Linq query below: var seq = (from n in GetObjects() select n.SomeKey) .Distinct() .Count(); This query works find with SQL Server 2005 and above. But, this start to give headache when I hooked the EF to SQL Server 2000. Because EF is using APPLY operator which only SQL Server 2005 and above can be supported. I do not know why the hell EF is using APPLy operator instead of sub queries. My current work around is: var seq = (from n in GetObjects() select n.SomeKey) .Distinct() .ToList() .Count(); But, I can forsee more problems to come. The above query is just a simple one. Did anyone come across such issue? And how you guys work around it? Or is there a way to force EF not to use APPLY operator? Any help will be very much appreciated. How Lun.

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  • 2 table SQL Query weird results

    - by javArc
    Ok this is driving me nuts, I need to write an SQL query that will grab product information from 2 tables. The first table 'products' contains the productId, productname, quantityperunit and unitprice. Now I can search by productname and categoryname individually, but when I try to combine the 2 I get crazy results, Here's the query: "SELECT DISTINCT productId, productname, quantityperunit, unitprice FROM products pr, categories ca WHERE pr.categoryID = ca.categoryID AND ProductName LIKE '%" + searchTerm + "%' OR CategoryName LIKE '%" + searchTerm + "%' excuse the java style in there, here it is formatted better: SELECT DISTINCT productId, productname, quantityperunit, unitprice FROM products pr, categories ca WHERE pr.categoryID = ca.categoryID AND ProductName LIKE 'Tofu' OR CategoryName LIKE 'Tofu' any help would be appreciated.

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  • MySql Union not getting executed in a view

    - by aLL0i
    Hi, I am trying to create a view for a UNION of 2 select statements that I have created. The UNION is working fine when executed individually But the problem is only the 1st part of the UNION is getting executed when I am executing it as a view. The query I am using is as below SELECT DISTINCT products.pid AS id, products.pname AS name, products.p_desc AS description, products.p_loc AS location, products.p_uid AS userid, products.isaproduct AS whatisit FROM products UNION SELECT DISTINCT services.s_id AS id, services.s_name AS name, services.s_desc AS description, services.s_uid AS userid, services.s_location AS location, services.isaservice AS whatisit FROM services WHERE services.s_name The above works fine when i execute it separately. But when I use it as a view, it does not give me the results of the services part. Could someone please help me with this?

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  • Analytic functions – they’re not aggregates

    - by Rob Farley
    SQL 2012 brings us a bunch of new analytic functions, together with enhancements to the OVER clause. People who have known me over the years will remember that I’m a big fan of the OVER clause and the types of things that it brings us when applied to aggregate functions, as well as the ranking functions that it enables. The OVER clause was introduced in SQL Server 2005, and remained frustratingly unchanged until SQL Server 2012. This post is going to look at a particular aspect of the analytic functions though (not the enhancements to the OVER clause). When I give presentations about the analytic functions around Australia as part of the tour of SQL Saturdays (starting in Brisbane this Thursday), and in Chicago next month, I’ll make sure it’s sufficiently well described. But for this post – I’m going to skip that and assume you get it. The analytic functions introduced in SQL 2012 seem to come in pairs – FIRST_VALUE and LAST_VALUE, LAG and LEAD, CUME_DIST and PERCENT_RANK, PERCENTILE_CONT and PERCENTILE_DISC. Perhaps frustratingly, they take slightly different forms as well. The ones I want to look at now are FIRST_VALUE and LAST_VALUE, and PERCENTILE_CONT and PERCENTILE_DISC. The reason I’m pulling this ones out is that they always produce the same result within their partitions (if you’re applying them to the whole partition). Consider the following query: SELECT     YEAR(OrderDate),     FIRST_VALUE(TotalDue)         OVER (PARTITION BY YEAR(OrderDate)               ORDER BY OrderDate, SalesOrderID               RANGE BETWEEN UNBOUNDED PRECEDING                         AND UNBOUNDED FOLLOWING),     LAST_VALUE(TotalDue)         OVER (PARTITION BY YEAR(OrderDate)               ORDER BY OrderDate, SalesOrderID               RANGE BETWEEN UNBOUNDED PRECEDING                         AND UNBOUNDED FOLLOWING),     PERCENTILE_CONT(0.95)         WITHIN GROUP (ORDER BY TotalDue)         OVER (PARTITION BY YEAR(OrderDate)),     PERCENTILE_DISC(0.95)         WITHIN GROUP (ORDER BY TotalDue)         OVER (PARTITION BY YEAR(OrderDate)) FROM Sales.SalesOrderHeader ; This is designed to get the TotalDue for the first order of the year, the last order of the year, and also the 95% percentile, using both the continuous and discrete methods (‘discrete’ means it picks the closest one from the values available – ‘continuous’ means it will happily use something between, similar to what you would do for a traditional median of four values). I’m sure you can imagine the results – a different value for each field, but within each year, all the rows the same. Notice that I’m not grouping by the year. Nor am I filtering. This query gives us a result for every row in the SalesOrderHeader table – 31465 in this case (using the original AdventureWorks that dates back to the SQL 2005 days). The RANGE BETWEEN bit in FIRST_VALUE and LAST_VALUE is needed to make sure that we’re considering all the rows available. If we don’t specify that, it assumes we only mean “RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW”, which means that LAST_VALUE ends up being the row we’re looking at. At this point you might think about other environments such as Access or Reporting Services, and remember aggregate functions like FIRST. We really should be able to do something like: SELECT     YEAR(OrderDate),     FIRST_VALUE(TotalDue)         OVER (PARTITION BY YEAR(OrderDate)               ORDER BY OrderDate, SalesOrderID               RANGE BETWEEN UNBOUNDED PRECEDING                         AND UNBOUNDED FOLLOWING) FROM Sales.SalesOrderHeader GROUP BY YEAR(OrderDate) ; But you can’t. You get that age-old error: Msg 8120, Level 16, State 1, Line 5 Column 'Sales.SalesOrderHeader.OrderDate' is invalid in the select list because it is not contained in either an aggregate function or the GROUP BY clause. Msg 8120, Level 16, State 1, Line 5 Column 'Sales.SalesOrderHeader.SalesOrderID' is invalid in the select list because it is not contained in either an aggregate function or the GROUP BY clause. Hmm. You see, FIRST_VALUE isn’t an aggregate function. None of these analytic functions are. There are too many things involved for SQL to realise that the values produced might be identical within the group. Furthermore, you can’t even surround it in a MAX. Then you get a different error, telling you that you can’t use windowed functions in the context of an aggregate. And so we end up grouping by doing a DISTINCT. SELECT DISTINCT     YEAR(OrderDate),         FIRST_VALUE(TotalDue)              OVER (PARTITION BY YEAR(OrderDate)                   ORDER BY OrderDate, SalesOrderID                   RANGE BETWEEN UNBOUNDED PRECEDING                             AND UNBOUNDED FOLLOWING),         LAST_VALUE(TotalDue)             OVER (PARTITION BY YEAR(OrderDate)                   ORDER BY OrderDate, SalesOrderID                   RANGE BETWEEN UNBOUNDED PRECEDING                             AND UNBOUNDED FOLLOWING),     PERCENTILE_CONT(0.95)          WITHIN GROUP (ORDER BY TotalDue)         OVER (PARTITION BY YEAR(OrderDate)),     PERCENTILE_DISC(0.95)         WITHIN GROUP (ORDER BY TotalDue)         OVER (PARTITION BY YEAR(OrderDate)) FROM Sales.SalesOrderHeader ; I’m sorry. It’s just the way it goes. Hopefully it’ll change the future, but for now, it’s what you’ll have to do. If we look in the execution plan, we see that it’s incredibly ugly, and actually works out the results of these analytic functions for all 31465 rows, finally performing the distinct operation to convert it into the four rows we get in the results. You might be able to achieve a better plan using things like TOP, or the kind of calculation that I used in http://sqlblog.com/blogs/rob_farley/archive/2011/08/23/t-sql-thoughts-about-the-95th-percentile.aspx (which is how PERCENTILE_CONT works), but it’s definitely convenient to use these functions, and in time, I’m sure we’ll see good improvements in the way that they are implemented. Oh, and this post should be good for fellow SQL Server MVP Nigel Sammy’s T-SQL Tuesday this month.

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  • Incremental Statistics Maintenance – what statistics will be gathered after DML occurs on the table?

    - by Maria Colgan
    Incremental statistics maintenance was introduced in Oracle Database 11g to improve the performance of gathering statistics on large partitioned table. When incremental statistics maintenance is enabled for a partitioned table, oracle accurately generated global level  statistics by aggregating partition level statistics. As more people begin to adopt this functionality we have gotten more questions around how they expected incremental statistics to behave in a given scenario. For example, last week we got a question around what partitions should have statistics gathered on them after DML has occurred on the table? The person who asked the question assumed that statistics would only be gathered on partitions that had stale statistics (10% of the rows in the partition had changed). However, what they actually saw when they did a DBMS_STATS.GATHER_TABLE_STATS was all of the partitions that had been affected by the DML had statistics re-gathered on them. This is the expected behavior, incremental statistics maintenance is suppose to yield the same statistics as gathering table statistics from scratch, just faster. This means incremental statistics maintenance needs to gather statistics on any partition that will change the global or table level statistics. For instance, the min or max value for a column could change after just one row is inserted or updated in the table. It might easier to demonstrate this using an example. Let’s take the ORDERS2 table, which is partitioned by month on order_date.  We will begin by enabling incremental statistics for the table and gathering statistics on the table. After the statistics gather the last_analyzed date for the table and all of the partitions now show 13-Mar-12. And we now have the following column statistics for the ORDERS2 table. We can also confirm that we really did use incremental statistics by querying the dictionary table sys.HIST_HEAD$, which should have an entry for each column in the ORDERS2 table. So, now that we have established a good baseline, let’s move on to the DML. Information is loaded into the latest partition of the ORDERS2 table once a month. Existing orders maybe also be update to reflect changes in their status. Let’s assume the following transactions take place on the ORDERS2 table this month. After these transactions have occurred we need to re-gather statistic since the partition ORDERS_MAR_2012 now has rows in it and the number of distinct values and the maximum value for the STATUS column have also changed. Now if we look at the last_analyzed date for the table and the partitions, we will see that the global statistics and the statistics on the partitions where rows have changed due to the update (ORDERS_FEB_2012) and the data load (ORDERS_MAR_2012) have been updated. The column statistics also reflect the changes with the number of distinct values in the status column increase to reflect the update. So, incremental statistics maintenance will gather statistics on any partition, whose data has changed and that change will impact the global level statistics.

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  • XNA Per-Polygon Collision Check

    - by user22985
    I'm working on a project in XNA for WP7 with a low-poly environment, my problem is I need to setup a working per-polygon collision check between 2 or more 3d meshes. I've checked tons of tutorials but all of them use bounding-boxes, bounding-spheres,rays etc., but what I really need is a VERY precise way of checking if the polygons of two distinct models have intersected or not. If you could redirect me to an example or at least give me some pointers I would be grateful.

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  • Why some consider static analysis a testing and some do not?

    - by user970696
    Preparing myself also to ISTQB certification, I found they call static analysis actually as a static testing, while some engineering book distinct between static analysis and testing, which is the dynamic activity. I tent to think that static analysis is not a testing in the true sense as it does not test, it checks/verifies. But sure I would love to hear opinion of the true experts here. Thank you

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  • Color schemes generation - theory and algorithms

    - by daniel.sedlacek
    Hi I will be generating charts and diagrams and I am looking for some theory on color schemes and algorithm examples. Example questions: How to generate complementary or analogous colors? How to generate pastel, cold and warm colors? How to generate any number of random but distinct colors? How to translate all that to the hex triplet (web color)? My implementation will be in AS3 but any examples in metacode are welcome.

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  • PTLQueue : a scalable bounded-capacity MPMC queue

    - by Dave
    Title: Fast concurrent MPMC queue -- I've used the following concurrent queue algorithm enough that it warrants a blog entry. I'll sketch out the design of a fast and scalable multiple-producer multiple-consumer (MPSC) concurrent queue called PTLQueue. The queue has bounded capacity and is implemented via a circular array. Bounded capacity can be a useful property if there's a mismatch between producer rates and consumer rates where an unbounded queue might otherwise result in excessive memory consumption by virtue of the container nodes that -- in some queue implementations -- are used to hold values. A bounded-capacity queue can provide flow control between components. Beware, however, that bounded collections can also result in resource deadlock if abused. The put() and take() operators are partial and wait for the collection to become non-full or non-empty, respectively. Put() and take() do not allocate memory, and are not vulnerable to the ABA pathologies. The PTLQueue algorithm can be implemented equally well in C/C++ and Java. Partial operators are often more convenient than total methods. In many use cases if the preconditions aren't met, there's nothing else useful the thread can do, so it may as well wait via a partial method. An exception is in the case of work-stealing queues where a thief might scan a set of queues from which it could potentially steal. Total methods return ASAP with a success-failure indication. (It's tempting to describe a queue or API as blocking or non-blocking instead of partial or total, but non-blocking is already an overloaded concurrency term. Perhaps waiting/non-waiting or patient/impatient might be better terms). It's also trivial to construct partial operators by busy-waiting via total operators, but such constructs may be less efficient than an operator explicitly and intentionally designed to wait. A PTLQueue instance contains an array of slots, where each slot has volatile Turn and MailBox fields. The array has power-of-two length allowing mod/div operations to be replaced by masking. We assume sensible padding and alignment to reduce the impact of false sharing. (On x86 I recommend 128-byte alignment and padding because of the adjacent-sector prefetch facility). Each queue also has PutCursor and TakeCursor cursor variables, each of which should be sequestered as the sole occupant of a cache line or sector. You can opt to use 64-bit integers if concerned about wrap-around aliasing in the cursor variables. Put(null) is considered illegal, but the caller or implementation can easily check for and convert null to a distinguished non-null proxy value if null happens to be a value you'd like to pass. Take() will accordingly convert the proxy value back to null. An advantage of PTLQueue is that you can use atomic fetch-and-increment for the partial methods. We initialize each slot at index I with (Turn=I, MailBox=null). Both cursors are initially 0. All shared variables are considered "volatile" and atomics such as CAS and AtomicFetchAndIncrement are presumed to have bidirectional fence semantics. Finally T is the templated type. I've sketched out a total tryTake() method below that allows the caller to poll the queue. tryPut() has an analogous construction. Zebra stripping : alternating row colors for nice-looking code listings. See also google code "prettify" : https://code.google.com/p/google-code-prettify/ Prettify is a javascript module that yields the HTML/CSS/JS equivalent of pretty-print. -- pre:nth-child(odd) { background-color:#ff0000; } pre:nth-child(even) { background-color:#0000ff; } border-left: 11px solid #ccc; margin: 1.7em 0 1.7em 0.3em; background-color:#BFB; font-size:12px; line-height:65%; " // PTLQueue : Put(v) : // producer : partial method - waits as necessary assert v != null assert Mask = 1 && (Mask & (Mask+1)) == 0 // Document invariants // doorway step // Obtain a sequence number -- ticket // As a practical concern the ticket value is temporally unique // The ticket also identifies and selects a slot auto tkt = AtomicFetchIncrement (&PutCursor, 1) slot * s = &Slots[tkt & Mask] // waiting phase : // wait for slot's generation to match the tkt value assigned to this put() invocation. // The "generation" is implicitly encoded as the upper bits in the cursor // above those used to specify the index : tkt div (Mask+1) // The generation serves as an epoch number to identify a cohort of threads // accessing disjoint slots while s-Turn != tkt : Pause assert s-MailBox == null s-MailBox = v // deposit and pass message Take() : // consumer : partial method - waits as necessary auto tkt = AtomicFetchIncrement (&TakeCursor,1) slot * s = &Slots[tkt & Mask] // 2-stage waiting : // First wait for turn for our generation // Acquire exclusive "take" access to slot's MailBox field // Then wait for the slot to become occupied while s-Turn != tkt : Pause // Concurrency in this section of code is now reduced to just 1 producer thread // vs 1 consumer thread. // For a given queue and slot, there will be most one Take() operation running // in this section. // Consumer waits for producer to arrive and make slot non-empty // Extract message; clear mailbox; advance Turn indicator // We have an obvious happens-before relation : // Put(m) happens-before corresponding Take() that returns that same "m" for T v = s-MailBox if v != null : s-MailBox = null ST-ST barrier s-Turn = tkt + Mask + 1 // unlock slot to admit next producer and consumer return v Pause tryTake() : // total method - returns ASAP with failure indication for auto tkt = TakeCursor slot * s = &Slots[tkt & Mask] if s-Turn != tkt : return null T v = s-MailBox // presumptive return value if v == null : return null // ratify tkt and v values and commit by advancing cursor if CAS (&TakeCursor, tkt, tkt+1) != tkt : continue s-MailBox = null ST-ST barrier s-Turn = tkt + Mask + 1 return v The basic idea derives from the Partitioned Ticket Lock "PTL" (US20120240126-A1) and the MultiLane Concurrent Bag (US8689237). The latter is essentially a circular ring-buffer where the elements themselves are queues or concurrent collections. You can think of the PTLQueue as a partitioned ticket lock "PTL" augmented to pass values from lock to unlock via the slots. Alternatively, you could conceptualize of PTLQueue as a degenerate MultiLane bag where each slot or "lane" consists of a simple single-word MailBox instead of a general queue. Each lane in PTLQueue also has a private Turn field which acts like the Turn (Grant) variables found in PTL. Turn enforces strict FIFO ordering and restricts concurrency on the slot mailbox field to at most one simultaneous put() and take() operation. PTL uses a single "ticket" variable and per-slot Turn (grant) fields while MultiLane has distinct PutCursor and TakeCursor cursors and abstract per-slot sub-queues. Both PTL and MultiLane advance their cursor and ticket variables with atomic fetch-and-increment. PTLQueue borrows from both PTL and MultiLane and has distinct put and take cursors and per-slot Turn fields. Instead of a per-slot queues, PTLQueue uses a simple single-word MailBox field. PutCursor and TakeCursor act like a pair of ticket locks, conferring "put" and "take" access to a given slot. PutCursor, for instance, assigns an incoming put() request to a slot and serves as a PTL "Ticket" to acquire "put" permission to that slot's MailBox field. To better explain the operation of PTLQueue we deconstruct the operation of put() and take() as follows. Put() first increments PutCursor obtaining a new unique ticket. That ticket value also identifies a slot. Put() next waits for that slot's Turn field to match that ticket value. This is tantamount to using a PTL to acquire "put" permission on the slot's MailBox field. Finally, having obtained exclusive "put" permission on the slot, put() stores the message value into the slot's MailBox. Take() similarly advances TakeCursor, identifying a slot, and then acquires and secures "take" permission on a slot by waiting for Turn. Take() then waits for the slot's MailBox to become non-empty, extracts the message, and clears MailBox. Finally, take() advances the slot's Turn field, which releases both "put" and "take" access to the slot's MailBox. Note the asymmetry : put() acquires "put" access to the slot, but take() releases that lock. At any given time, for a given slot in a PTLQueue, at most one thread has "put" access and at most one thread has "take" access. This restricts concurrency from general MPMC to 1-vs-1. We have 2 ticket locks -- one for put() and one for take() -- each with its own "ticket" variable in the form of the corresponding cursor, but they share a single "Grant" egress variable in the form of the slot's Turn variable. Advancing the PutCursor, for instance, serves two purposes. First, we obtain a unique ticket which identifies a slot. Second, incrementing the cursor is the doorway protocol step to acquire the per-slot mutual exclusion "put" lock. The cursors and operations to increment those cursors serve double-duty : slot-selection and ticket assignment for locking the slot's MailBox field. At any given time a slot MailBox field can be in one of the following states: empty with no pending operations -- neutral state; empty with one or more waiting take() operations pending -- deficit; occupied with no pending operations; occupied with one or more waiting put() operations -- surplus; empty with a pending put() or pending put() and take() operations -- transitional; or occupied with a pending take() or pending put() and take() operations -- transitional. The partial put() and take() operators can be implemented with an atomic fetch-and-increment operation, which may confer a performance advantage over a CAS-based loop. In addition we have independent PutCursor and TakeCursor cursors. Critically, a put() operation modifies PutCursor but does not access the TakeCursor and a take() operation modifies the TakeCursor cursor but does not access the PutCursor. This acts to reduce coherence traffic relative to some other queue designs. It's worth noting that slow threads or obstruction in one slot (or "lane") does not impede or obstruct operations in other slots -- this gives us some degree of obstruction isolation. PTLQueue is not lock-free, however. The implementation above is expressed with polite busy-waiting (Pause) but it's trivial to implement per-slot parking and unparking to deschedule waiting threads. It's also easy to convert the queue to a more general deque by replacing the PutCursor and TakeCursor cursors with Left/Front and Right/Back cursors that can move either direction. Specifically, to push and pop from the "left" side of the deque we would decrement and increment the Left cursor, respectively, and to push and pop from the "right" side of the deque we would increment and decrement the Right cursor, respectively. We used a variation of PTLQueue for message passing in our recent OPODIS 2013 paper. ul { list-style:none; padding-left:0; padding:0; margin:0; margin-left:0; } ul#myTagID { padding: 0px; margin: 0px; list-style:none; margin-left:0;} -- -- There's quite a bit of related literature in this area. I'll call out a few relevant references: Wilson's NYU Courant Institute UltraComputer dissertation from 1988 is classic and the canonical starting point : Operating System Data Structures for Shared-Memory MIMD Machines with Fetch-and-Add. Regarding provenance and priority, I think PTLQueue or queues effectively equivalent to PTLQueue have been independently rediscovered a number of times. See CB-Queue and BNPBV, below, for instance. But Wilson's dissertation anticipates the basic idea and seems to predate all the others. Gottlieb et al : Basic Techniques for the Efficient Coordination of Very Large Numbers of Cooperating Sequential Processors Orozco et al : CB-Queue in Toward high-throughput algorithms on many-core architectures which appeared in TACO 2012. Meneghin et al : BNPVB family in Performance evaluation of inter-thread communication mechanisms on multicore/multithreaded architecture Dmitry Vyukov : bounded MPMC queue (highly recommended) Alex Otenko : US8607249 (highly related). John Mellor-Crummey : Concurrent queues: Practical fetch-and-phi algorithms. Technical Report 229, Department of Computer Science, University of Rochester Thomasson : FIFO Distributed Bakery Algorithm (very similar to PTLQueue). Scott and Scherer : Dual Data Structures I'll propose an optimization left as an exercise for the reader. Say we wanted to reduce memory usage by eliminating inter-slot padding. Such padding is usually "dark" memory and otherwise unused and wasted. But eliminating the padding leaves us at risk of increased false sharing. Furthermore lets say it was usually the case that the PutCursor and TakeCursor were numerically close to each other. (That's true in some use cases). We might still reduce false sharing by incrementing the cursors by some value other than 1 that is not trivially small and is coprime with the number of slots. Alternatively, we might increment the cursor by one and mask as usual, resulting in a logical index. We then use that logical index value to index into a permutation table, yielding an effective index for use in the slot array. The permutation table would be constructed so that nearby logical indices would map to more distant effective indices. (Open question: what should that permutation look like? Possibly some perversion of a Gray code or De Bruijn sequence might be suitable). As an aside, say we need to busy-wait for some condition as follows : "while C == 0 : Pause". Lets say that C is usually non-zero, so we typically don't wait. But when C happens to be 0 we'll have to spin for some period, possibly brief. We can arrange for the code to be more machine-friendly with respect to the branch predictors by transforming the loop into : "if C == 0 : for { Pause; if C != 0 : break; }". Critically, we want to restructure the loop so there's one branch that controls entry and another that controls loop exit. A concern is that your compiler or JIT might be clever enough to transform this back to "while C == 0 : Pause". You can sometimes avoid this by inserting a call to a some type of very cheap "opaque" method that the compiler can't elide or reorder. On Solaris, for instance, you could use :"if C == 0 : { gethrtime(); for { Pause; if C != 0 : break; }}". It's worth noting the obvious duality between locks and queues. If you have strict FIFO lock implementation with local spinning and succession by direct handoff such as MCS or CLH,then you can usually transform that lock into a queue. Hidden commentary and annotations - invisible : * And of course there's a well-known duality between queues and locks, but I'll leave that topic for another blog post. * Compare and contrast : PTLQ vs PTL and MultiLane * Equivalent : Turn; seq; sequence; pos; position; ticket * Put = Lock; Deposit Take = identify and reserve slot; wait; extract & clear; unlock * conceptualize : Distinct PutLock and TakeLock implemented as ticket lock or PTL Distinct arrival cursors but share per-slot "Turn" variable provides exclusive role-based access to slot's mailbox field put() acquires exclusive access to a slot for purposes of "deposit" assigns slot round-robin and then acquires deposit access rights/perms to that slot take() acquires exclusive access to slot for purposes of "withdrawal" assigns slot round-robin and then acquires withdrawal access rights/perms to that slot At any given time, only one thread can have withdrawal access to a slot at any given time, only one thread can have deposit access to a slot Permissible for T1 to have deposit access and T2 to simultaneously have withdrawal access * round-robin for the purposes of; role-based; access mode; access role mailslot; mailbox; allocate/assign/identify slot rights; permission; license; access permission; * PTL/Ticket hybrid Asymmetric usage ; owner oblivious lock-unlock pairing K-exclusion add Grant cursor pass message m from lock to unlock via Slots[] array Cursor performs 2 functions : + PTL ticket + Assigns request to slot in round-robin fashion Deconstruct protocol : explication put() : allocate slot in round-robin fashion acquire PTL for "put" access store message into slot associated with PTL index take() : Acquire PTL for "take" access // doorway step seq = fetchAdd (&Grant, 1) s = &Slots[seq & Mask] // waiting phase while s-Turn != seq : pause Extract : wait for s-mailbox to be full v = s-mailbox s-mailbox = null Release PTL for both "put" and "take" access s-Turn = seq + Mask + 1 * Slot round-robin assignment and lock "doorway" protocol leverage the same cursor and FetchAdd operation on that cursor FetchAdd (&Cursor,1) + round-robin slot assignment and dispersal + PTL/ticket lock "doorway" step waiting phase is via "Turn" field in slot * PTLQueue uses 2 cursors -- put and take. Acquire "put" access to slot via PTL-like lock Acquire "take" access to slot via PTL-like lock 2 locks : put and take -- at most one thread can access slot's mailbox Both locks use same "turn" field Like multilane : 2 cursors : put and take slot is simple 1-capacity mailbox instead of queue Borrow per-slot turn/grant from PTL Provides strict FIFO Lock slot : put-vs-put take-vs-take at most one put accesses slot at any one time at most one put accesses take at any one time reduction to 1-vs-1 instead of N-vs-M concurrency Per slot locks for put/take Release put/take by advancing turn * is instrumental in ... * P-V Semaphore vs lock vs K-exclusion * See also : FastQueues-excerpt.java dice-etc/queue-mpmc-bounded-blocking-circular-xadd/ * PTLQueue is the same as PTLQB - identical * Expedient return; ASAP; prompt; immediately * Lamport's Bakery algorithm : doorway step then waiting phase Threads arriving at doorway obtain a unique ticket number Threads enter in ticket order * In the terminology of Reed and Kanodia a ticket lock corresponds to the busy-wait implementation of a semaphore using an eventcount and a sequencer It can also be thought of as an optimization of Lamport's bakery lock was designed for fault-tolerance rather than performance Instead of spinning on the release counter, processors using a bakery lock repeatedly examine the tickets of their peers --

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  • Update to 13.10: blank screen and repeated suspend on wake from suspend

    - by user208026
    After updating from 13.04 to 13.10, intermittently when awaking from suspend, my screen will blink to black screen a few times, offer a login screen, and then go back to suspend unexpectedly. This will repeat each time I subsequently awake it from suspend. Only a restart will escape the suspend loop. This issue arose in tandem with the already raised issue regarding networking not restarting on wake from suspend, though appears to be distinct from that issue.

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  • The role of the Infrastructure DBA

    - by GavinPayneUK
    Do you have someone performing an Infrastructure DBA role within your organisation? Do you realise why today you now might need one? When I first started working with SQL Server there were three distinct roles in the SQL Server virtual team: developer , DBA and sysadmin . In my simple terms, the developer looked after the “code”: the schema, stored procedures, and any ETL to get data in, out or updated within the database. They could talk in business entity terms about Customer numbers, Product codes...(read more)

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  • Oracle ERP Cloud Solution Defines Revenue Recognition Software Market

    - by Steve Dalton
    Normal 0 false false false EN-US X-NONE X-NONE Revenue is a fundamental yardstick of a company's performance, and one of the most important metrics for investors in the capital markets. So it’s no surprise that the accounting standard boards have devoted significant resources to this topic, with a key goal of ensuring that companies use a consistent method of recognizing revenue. Due to the myriad of revenue-generating transactions, and the divergent ways organizations recognize revenue today, the IFRS and FASB have been working for 12 years on a common set of accounting standards that apply to all industries in virtually all countries. Through their joint efforts on May 28, 2014 the FASB and IFRS released the IFRS 15 / ASU 2014-9 (Revenue from Contracts with Customers) converged accounting standard. This standard applies to revenue in all public companies, but heavily impacts organizations in any industry that might have complex sales contracts with multiple distinct deliverables (obligations). For example, an auto dealer who bundles free service with the sale of a car can only recognize the service revenue once the owner of the car brings it in for work. Similarly, high-tech companies that bundle software licenses, consulting, and support services on a sales contract will recognize bundled service revenue once the services are delivered. Now all companies need to review their revenue for hidden bundling and implicit obligations. Numerous time-consuming and judgmental activities must be performed to properly recognize revenue for complex sales contracts. To illustrate, after the contract is identified, organizations must identify and examine the distinct deliverables, determine the estimated selling price (ESP) for each deliverable, then allocate the total contract price to each deliverable based on the ESPs. In terms of accounting, organizations must determine whether the goods or services have been delivered or performed to the customer’s satisfaction, then either book revenue in the current period or record a liability for the obligation if revenue will be recognized in a future accounting period. Oracle Revenue Management Cloud was architected and developed so organizations can simplify and streamline revenue recognition. Among other capabilities, the solution uses business rules to efficiently identify and examine contracts, intelligently calculate and allocate deliverable prices based on prescribed inputs, and accurately recognize revenue for each deliverable based on customer satisfaction. "Oracle works very closely with our customers, the Big 4 accounting firms, and the accounting standard boards to deliver an adaptive, comprehensive, new generation revenue recognition solution,” said Rondy Ng, Senior Vice President, Applications Development. “With the recently announced IFRS 15 / ASU 2014-9, Oracle is ready to support customer adoption of the new standard with our Revenue Management Cloud,” said Rondy. Oracle Revenue Management Cloud, an integral part of Oracle Financials Cloud, helps organizations comply with accounting standards, provides them with confidence that reported revenue is materially accurate, and simplifies the accounting process for revenue recognition. Stay tuned to this blog for regular updates on Oracle Revenue Management Cloud. We also invite you to review our new oracle.com ERP pages @ oracle.com/erp. We will be updating these pages very soon with more information about Oracle Revenue Management Cloud.

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  • How to fix a Silverlight download progress indicator that jumps from 0% to 100%

    - by JaydPage
    Originally posted on: http://geekswithblogs.net/JaydPage/archive/2013/10/29/fixing-a-broken-silverlight-xap-file-download-progress-indicator-that.aspxAfter moving our silverlight application to a new server I came across an problem whereby the download progress indicator on the splash screen was stuck on 0% until the file had completely downloaded.After about an hour of searching for the answer I realised that there is a distinct lack of help out there for this problem.It is a simple fix:1) On the server that is hosting your website, go into IIS and click on the website.2) Click on the compression section3) Un-check the option that says "Dynamic Content Compression"4) Save changes

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  • Oracle University: Database 11g Certification News(Week 39)

    - by rituchhibber
    The following exam has recently become available for beta testing: Exam Title (and code) Certification Track Oracle Database 11g Release 2: SQL Tuning  (1Z1-117) Oracle Certified Expert, Oracle Database 11g Release 2 SQL Tuning Full preparation details are available on the exam page, including prerequisites for this certification, exam topics and pricing. Remember: Your OPN discount is applied to the standard pricing shown on the website.A beta exam offers you two distinct advantages: you will be one of the first to get certified you pay a lower price. Beta exams can be taken at any Pearson VUE Testing Center.

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  • Is it possible to efficiently store all possible phone numbers in memory?

    - by Spencer K
    Given the standard North American phone number format: (Area Code) Exchange - Subscriber, the set of possible numbers is about 6 billion. However, efficiently breaking down the nodes into the sections listed above would yield less than 12000 distinct nodes that can be arranged in groupings to get all the possible numbers. This seems like a problem already solved. Would it done via a graph or tree?

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  • Stay Connected To Friends With Free SMS

    Online SMSs have received mass acceptance today. Though it is distinct in many ways from a mobile phone, it has its own advantages. In today?s fast paced life, people are left with really less time... [Author: Pooja Singh - Computers and Internet - March 29, 2010]

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  • Why can we recognize game engines?

    - by Bart van Heukelom
    About many games you can say "oh that's the Unreal engine for sure", "this was made by upgrading GTA 4", etc. We can often recognize the engine used for a game just by looking at its graphics (disregarding menus and such). I'm wondering, why is this? All game engines use the same 3D rendering technology that we all use, and the different games usually have a distinct art style, so what's left to recognize?

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  • Isn't MVC anti OOP?

    - by m3th0dman
    The main idea behind OOP is to unify data and behavior in a single entity - the object. In procedural programming there is data and separately algorithms modifying the data. In the Model-View-Controller pattern the data and the logic/algorithms are placed in distinct entities, the model and the controller respectively. In an equivalent OOP approach shouldn't the model and the controller be placed in the same logical entity?

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  • Updates about Multidimensional vs Tabular #ssas #msbi

    - by Marco Russo (SQLBI)
    I recently read the blog post from James Serra Tabular model: Not ready for prime time? (read also the comments because there are discussions about a few points raised by James) and the following post from Christian Wade Multidimensional or Tabular. In the last 2 years I worked with many companies adopting Tabular in different scenarios and I agree with some of the points expressed by James in his post (especially about missing features in Tabular if compared to Multidimensional), but I strongly disagree in others. In general, Tabular is a good choice for a new project when: the development team does not have a good knowledge of Multidimensional and MDX (DAX is faster to learn, not so easy as it is sold by MS, but definitely easier than MDX) you don’t need calculations based on hierarchies (common in certain financial applications, but not so common as it could seem) there are important calculations based on distinct count measures there are complex calculations based on many-to-many relationships Until now, I never suggested to migrate an existing Multidimensional model to a Tabular one. There should be very important reasons for that, such as performance issues in distinct count and many-to-many relationships that cannot be easily solved by optimizing the Multidimensional model, but I still never encountered this scenario. I would say that in 80% of the new projects, you might use either Multidimensional or Tabular and the real difference is the time-to-market depending on the skills of the development team. So it’s not strange that who is used to Multidimensional is not moving to Tabular, not getting a particular benefit from the new model unless specific requirements exist. The recent DAXMD feature that allows using SharePoint Power View on Multidimensional is a really important one, even if I’d like having also Excel Power View enabled for this scenario (this should be just a question of time). Another scenario in which I’m seeing a growing adoption of Tabular is in companies that creates models for their product/service and do that by using XMLA or Tabular AMO 2012. I am used to call them ISVs, even if those providing services cannot be really defined in this way. These companies are facing the multitenancy challenge with Tabular and even if this is a niche market, I see some potential here, because adopting Tabular seems a much more natural choice than Multidimensional in those scenario where an analytical engine has to be embedded to deliver one of the features of a larger product/service delivered to customers. I’d like to see other feedbacks in the comments: tell your story of choosing between Tabular and Multidimensional in a BI project you started with SQL Server 2012, thanks!

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  • Applying Advanced Search Operators

    Search engines have developed additional applications termed advanced search operators to offer power internet marketers even more control each time searching. Advanced search operators are exclusive terms which you could place as part of your search query in order to come across unique sorts of details which a common search can not offer. A number of of those operators provide valuable tools for SEO specialists as well as other people who desire rather specific details, or maybe who need to restrict their particular search to extremely distinct source.

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  • Membership Website - 6 Success Strategies to Implement

    Here are some strategies that have helped me create a highly profitable membership website and can help you do the same. Make your membership website a continuity program. Not all membership websites are continuity programs, some have a course format and have a distinct beginning and ending.

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  • Filling array with numbers from given range so that sum of adjacent numbers is square number

    - by REACHUS
    Problem: Fill all the cells using distinct numbers from <1,25 set, so that sum of two adjacent cells is a square number. (source: http://grymat.im.pwr.wroc.pl/etap1/zad1etp1213.pdf; numbers 20 and 13 have been given) I've already solved this problem analytically and now I would like to approach it using an algorithm. I would like to know how should I approach these kind of problems in general (not a solution, just a point for me to start).

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